Remote Sensing

Remote sensing provides information about objects at or near the surface of the earth and atmosphere based on radiation reflected or emitted from those objects. The information is typically captured at a distance from above in the form of image data. Such data allow us to determine the composition and nature of the earth's surface and atmosphere from local to global scales, and assess changes by analyzing images captured at different points in time. In this sense, remote sensing is useful in providing spatial information that is otherwise difficult or impossible to obtain. In the social sciences remote sensing is useful for visualizing (providing alternative and synoptic views) and classifying human environments. Social science researchers commonly integrate remotely sensed data or its derivatives with other socioeconomic datasets within geographic information systems (GIS) to conduct spatial analyses. Today, unpiloted aerial vehicles (UAVs, drones) are revolutionizing the way that imagery of earth is captured, however traditional methods remain important. This entry reviews the history and principles of remote sensing, and presents common types of analysis and social science applications of remotely sensed data.